Alle Publikationen
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2018
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(2018): Towards a framework for computational persuasion with applications in behaviour change1. In: Argument & Computation 9 (1), S. 15-40. DOI: 10.3233/AAC-170032
DOI: https://doi.org/10.3233/AAC-170032 Abstract: Persuasion is an activity that involves one party trying to induce another party to believe something or to do something. It is an important and multifaceted human facility. Obviously, sales and marketing is heavily dependent on persuasion. But many other activities involve persuasion such as a doctor persuading a patient to drink less alcohol, a road safety expert persuading drivers to not text while driving, or an online safety expert persuading users of social media sites to not reveal too much personal information online. As computing becomes involved in every sphere of life, so too is persuasion a target for applying computer-based solutions. An automated persuasion system (APS) is a system that can engage in a dialogue with a user (the persuadee) in order to persuade the persuadee to do (or not do) some action or to believe (or not believe) something. To do this, an APS aims to use convincing arguments in order to persuade the persuadee. Computational persuasion is the study of formal models of dialogues involving arguments and counterarguments, of user models, and strategies, for APSs. A promising application area for computational persuasion is in behaviour change. Within healthcare organizations, government agencies, and non-governmental agencies, there is much interest in changing behaviour of particular groups of people away from actions that are harmful to themselves and/or to others around them.
Keywords: Argumentation, argumentation strategies, Argumentationsstrategie, Argumentationstheorie, automated persuasion system (APS), Automated Persuasion Systems (APS), computational models of argument, Computational persuasion, Computerbasierte Persuasion, dialogical argumentation, doppelter Treffer, Eliminierung von Fehlverhalten, Fehlverhalten, frame semantics, Gesellschaftsprofit, Gruppenverhalten / Joint Action, Intellektualtechnik, Kognitionstheorie, Kognitionswissenschaft/Social Sciences/Humanities, Mensch-Technik-Relationen (MTR), Observablen/Kriterien für sozial angemessenes Verhalten und dessen Bewertung, Persuasion, persuasion dialogues, persuasive arguments, Politik, probabilistic argumentation, Realtechnik, Soziale Angemessenheit, Sozialer Raum / Kultureller Kontext, Sprachroboter, Sprachverarbeitung, Technik, Überreden, Überzeugung, Umgangsformen, Verführung 2017
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(2017) : Strategies and mechanisms to enable dialogue agents to respond appropriately to indirect speech acts In: IEEE Ro-Man: Human-robot collaboration and human assistance for an improved quality of life: IEEE RO-MAN 2017 : 26th IEEE International Symposium on Robot and Human Ineractive Communication : August 28-September 1, 2017, Lisbon, Portugal: Piscataway, NJ: IEEE, S. 323-328
Abstract: Humans often use indirect speech acts (ISAs) when issuing directives. Much of the work in handling ISAs in computational dialogue architectures has focused on correctly identifying and handling the underlying non-literal meaning. There has been less attention devoted to how linguistic responses to ISAs might differ from those given to literal directives and how to enable different response forms in these computational dialogue systems. In this paper, we present ongoing work toward developing dialogue mechanisms within a cognitive, robotic architecture that enables a richer set of response strategies to non-literal directives.
Keywords: Antworten im Rahmen einer Konversation, Computerwissenschaft, indirect speech acts, Indirektheit, Informations- & Kommunikationstechnik, Interaktionspartner, Konversationsanalyse, Korrespondenz, Künstliche Intelligenz, Linguistik, Mensch oder Maschine, Mensch-Technik-Relationen (MTR), nicht wörtlich, non-literal meaning, Realtechnik, Semantik, Soziale Robotik, Sprachgebrauch, Sprachroboter, Sprachverarbeitung, Sprechakt, Technik, Unterschiedliche Antworten je nach Direktheit/Indirektheit des vorherigen Sprechaktes -
(2017): Making sense of words. A robotic model for language abstraction. In: Autonomous Robots 41 (2), S. 367-383. DOI: 10.1007/s10514-016-9587-8
Abstract: Building robots capable of acting independently in unstructured environments is still a challenging task for roboticists. The capability to comprehend and produce language in a 'human-like' manner represents a powerful tool for the autonomous interaction of robots with human beings, for better understanding situations and exchanging information during the execution of tasks that require cooperation. In this work, we present a robotic model for grounding abstract action words (i.e. USE, MAKE) through the hierarchical organization of terms directly linked to perceptual and motor skills of a humanoid robot. Experimental results have shown that the robot, in response to linguistic commands, is capable of performing the appropriate behaviors on objects. Results obtained in case of inconsistency between the perceptual and linguistic inputs have shown that the robot executes the actions elicited by the seen object.
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